CS 279
Computational Biology:
Structure and Organization of Biomolecules and Cells
(cross-listed as BIOMEDIN 279, BIOPHYS 279, and CME 279)
Course Information
Description:
This course will focus on computational techniques used to study the structure and dynamics of
biomolecules, cells, and everything in between. For example, what is the structure of proteins, DNA,
and RNA, and how do their motions contribute to their function? How are molecules distributed and
compartmentalized within a cell, and how do they move around? How might one modify the behavior
of these systems using drugs or other therapeutics? How can structural information contribute to the
design of drugs, proteins, or perhaps even cells?
Computation can contribute to addressing such questions in at least two distinct ways. First, one can
use computational analysis to extract information from experimental measurements, and to interpret
and combine the results of such experiments. Second, one can use physical principles to predict
structure or simulate motion.
The first part of the course will cover atomic-level molecular modeling methods for proteins and
other biomolecules, including structure determination and prediction, molecular dynamics simulation,
docking, and protein design. The second part will cover techniques for determining structures or
structural properties of macromolecular complexes – for example, through cryoelectron microscopy.
The third part will cover the cellular level of spatial organization, including computational analysis of
optical microscopy images and video, and simulations at the cellular scale. The course will cover both
foundational material and cutting-edge research in each of these areas.
Coursework:
Students will be expected to complete three assignments, each
of which will involve a combination of theoretical questions and computer work. Students will also
be expected to complete a project. The project will involve about as much work as an
assignment, but it will be more open-ended and will allow students to delve into a topic of their
choosing in more depth.
Prerequisites:
Elementary Programming Background (at the level of 106A),
Introductory Course in Biology
Instructor: Ron Dror
- Office Hours:
Thursday 4:20 - 6:00 PM in Gates 204, or by appointment.
TA: Osama El-Gabalawy
- Office Hours:
- Tuesdays from 4:20 - 5:10 PM in Econ 140
- Wednesdays from 10:30 AM - 12:00 PM in Lathrop Tech Lounge
- Thursdays 1:20 - 3:00 PM in Lathrop Tech Lounge
TA: Quinlan Jung
Contact:
Please use Piazza for questions related to lectures and assignments.
If you have issues that cannot be resolved on Piazza, please contact us at
cs279-aut1516-staff@lists.
Class: Tuesday - Thursday 3:00 PM - 4:20 PM, Econ 140 (Landau Economics Building)
Announcements: All announcements will be made on Piazza.
Materials:
There is no required textbook. We will suggest a variety of optional
reading material throughout the course.
Exam:
There will be a final exam held on
Tuesday, December 8, 2015 from 3:30 PM - 5:30 PM in Herrin Hall (Biology), Room T175.
Handouts
Lectures
- 9/22 - Introduction [slides] [notes]
- 9/24 and 9/29 - Protein Structure [slides]
Optional Reading:
- 9/29 and 10/1 - Energy Functions and their relationship to protein conformation [slides]
Optional Reading:
- 10/6 and 10/8 - Molecular Dynamics Simulation [slides]
Optional Reading:
- 10/13 and 10/15 - Protein Structure Prediction [slides]
Optional Reading:
- 10/20 and 10/22 - Protein Design [slides]
Optional Reading:
- 10/22 and 10/27 - Ligand Docking [slides]
Optional Reading:
- 10/27 and 10/29 - Fourier Transforms and Convolution [slides] [FT notes] [Convolution notes]
- 10/29 and 11/3 - Image Analysis [slides] [notes]
- 11/05 - Microscopy [slides]
Optional Reading:
- 11/05 and 11/10 - Diffusion [slides]
Optional Reading:
- 11/10 - Project Ideas [slides]
- 11/12 - X-Ray Crystallography [slides] [notes]
- 11/17 and 11/19 - Single-particle electron microscopy [slides]
Optional Reading:
- 12/1 and 12/3 - Review [slides]
Assignments
Python Resources
In this class, the programming assignments will be in Python. If you have prior experience with Python, great! If you don't, no worries! All we expect is that you're familiar with basic programming. That said, if you've never worked with Python before, it may be helpful to look at some of the following resources to help you get up to speed.
- Codecademy is a site that does a good job of introducing the basics of Python, organized by topic. If you're just getting started with Python or if you want to brush up on specific issues, this may be helpful.
- BMI 214 is another class on computational biology. They have put together a python tutorial for their class, which gives a great overview of Python's functionality.
- Check out CME 193: Introduction to Scientific Python! It's a 1-unit course that runs for four weeks, beginning in the second week of the quarter. It is recommended for students who want to use Python in math, science, or engineering courses and for students who want to learn the basics of Python programming.
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